A Five Year Randomized Controlled Trial to Assess the Efficacy and Antibody Responses to a Commercial and Autogenous Vaccine for the Prevention of Infectious Bovine Keratoconjunctivitis

Early detection of infectious bovine keratoconjunctivitis with artificial intelligence

Artificial intelligence (AI) was developed to distinguish cattle by their muzzle patterns and identify early cases of disease, including infectious bovine keratoconjunctivitis (IBK). It was tested on 870 cattle in four locations, with 170 developing IBK. The AI identified 169 of the 170 cases prior to their identification by veterinarians, and another 17 cases that remained free of IBK signs (sensitivity = 99.4%, specificity = 97.6%). These results indicate the AI can detect emerging IBK cases by muzzle images very early in the disease process and be used as an intervention tool in the prevention of IBK outbreaks.

Alterations to the bovine bacterial ocular surface microbiome in the context of infectious bovine keratoconjunctivitis

BACKGROUND

Infectious bovine keratoconjunctivitis (IBK) is a common cause of morbidity in cattle, resulting in significant economic losses. This study aimed to characterize the bovine bacterial ocular surface microbiome (OSM) through conjunctival swab samples from Normal eyes and eyes with naturally acquired, active IBK across populations of cattle using a three-part approach, including bacterial culture, relative abundance (RA, 16 S rRNA gene sequencing), and semi-quantitative random forest modeling (real-time polymerase chain reaction (RT-PCR)).

RESULTS

Conjunctival swab samples were obtained from eyes individually classified as Normal (n = 376) or IBK (n = 228) based on clinical signs. Cattle unaffected by IBK and the unaffected eye in cattle with contralateral IBK were used to obtain Normal eye samples. Moraxella bovis was cultured from similar proportions of IBK (7/228, 3.07%) and Normal eyes (1/159, 0.63%) (p = 0.1481). Moraxella bovoculi was cultured more frequently (p < 0.0001) in IBK (59/228, 25.88%) than Normal (7/159, 4.40%) eyes. RA (via 16 S rRNA gene sequencing) of Actinobacteriota was significantly higher in Normal eyes (p = 0.0045). Corynebacterium variabile and Corynebacterium stationis (Actinobacteriota) were detected at significantly higher RA (p = 0.0008, p = 0.0025 respectively) in Normal eyes. Rothia nasimurium (Actinobacteriota) was detected at significantly higher RA in IBK eyes (p < 0.0001). Alpha-diversity index was not significantly different between IBK and Normal eyes (p > 0.05). Alpha-diversity indices for geographic location (p < 0.001), age (p < 0.0001), sex (p < 0.05) and breed (p < 0.01) and beta-diversity indices for geographic location (p < 0.001), disease status (p < 0.01), age (p < 0.001), sex (p < 0.001) and breed (p < 0.001) were significantly different between groups. Modeling of RT-PCR values reliably categorized the microbiome of IBK and Normal eyes; primers for Moraxella bovoculi, Moraxella bovis, and Staphylococcus spp. were consistently the most significant canonical variables in these models.

CONCLUSIONS

The results provide further evidence that multiple elements of the bovine bacterial OSM are altered in the context of IBK, indicating the involvement of a variety of bacteria in addition to Moraxella bovis, including Moraxella bovoculi and R. nasimurium, among others. Actinobacteriota RA is altered in IBK, providing possible opportunities for novel therapeutic interventions. While RT-PCR modeling provided limited further support for the involvement of Moraxella bovis in IBK, this was not overtly reflected in culture or RA results. Results also highlight the influence of geographic location and breed type (dairy or beef) on the bovine bacterial OSM. RT-PCR modeling reliably categorized samples as IBK or Normal.

Detection of Mannheimia haemolytica-Specific IgG, IgM and IgA in Sera and Their Relationship to Respiratory Disease in Cattle

Mannheimia haemolytica is one of the major causes of bovine respiratory disease in cattle. The organism is the primary bacterium isolated from calves and young cattle affected with enzootic pneumonia. Novel indirect ELISAs were developed and evaluated to enable quantification of antibody responses to whole cell antigens using M. haemolytica A1 strain P1148. In this study, the ELISAs were initially developed using sera from both M. haemolytica-culture-free and clinically infected cattle, then the final prototypes were tested in the validation phase using a larger set of known-status M. haemolytica sera (n = 145) collected from feedlot cattle. The test showed good inter-assay and intra-assay repeatability. Diagnostic sensitivity and specificity were estimated at 91% and 87% for IgG at a cutoff of S/P ≥ 0.8. IgM diagnostic sensitivity and specificity were 91% and 81% at a cutoff of sample to positive (S/P) ratio ≥ 0.8. IgA diagnostic sensitivity was 89% whereas specificity was 78% at a cutoff of S/P ≥ 0.2. ELISA results of all isotypes were related to the diagnosis of respiratory disease and isolation of M. haemolytica (p-value < 0.05). These data suggest that M. haemolytica ELISAs can be adapted to the detection and quantification of antibody in serum specimens and support the use of these tests for the disease surveillance and disease prevention research in feedlot cattle.

Genotype classification of Moraxella bovis using MALDI-TOF MS profiles

Moraxella bovis (M. bovis) is regarded as a causative agent of infectious bovine keratoconjunctivitis (IBK), the most common ocular disease of cattle. Recently, whole genome sequencing identified the presence of two distinct genotypes within M. bovis that differ in chromosome content, potential virulence factors, as well as prophage and plasmid profiles. It is unclear if the genotypes equally associate with IBK or if one is more likely to be isolated from IBK lesions. We utilized 39 strains of M. bovis that had previously undergone whole genome sequencing and genotype classification to determine the utility of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) to accurately genotype M. bovis strains. We successfully developed two biomarker models that accurately classified strains according to genotype with an overall accuracy of 85.8-100% depending upon the model and sample preparation method used. These models provide a practical tool to enable studies of genotype associations with disease, allow for epidemiological studies at the sub-species level, and can be used to enhance disease prevention strategies.